News
10/18/25: 96 total papers have been accepted to our workshop! See them on here on OpenReview!
10/10/25: the camera-ready deadline for accepted papers is November 23, 2025 (Anywhere on Earth). Please make sure to upload your final version by this date.
9/1/25: Due to systematic OpenReview issues, we are extending the deadline to September 2, 2025 AOE. We have messaged OpenReview to ask them when it can be brought back online.
8/1/25: Thanks to strong community support, we are extending the submission deadline to September 1, 2025. We are looking forward to reading your work!
Time-series data underpin modern healthcare, spanning electronic health records, physiological waveforms, wearables, and population trends, yet their unique characteristics—including uncertain ground truth, quasi-periodic physiological motifs, and non-semantic timepoints—demand specialized machine learning approaches. While recent advances in foundation models, multimodal learning, and generative methods show promise, significant challenges remain in causality, interpretability, and deployment.
Our TS4H workshop unites researchers across health time-series domains (from wearables to clinical systems) to address shared challenges through: (1) cross-domain discussion, (2) diverse industry/academic perspectives (featuring Google, Oura, Apple and 5 institutions), and (3) community engagement via posters, talks, and panels. By fostering cross-domain collaboration on physiological-aware methods, we aim to bridge the gap between cutting-edge ML and real-world healthcare impact.
To recognize an outstanding contribution, we are pleased to offer a $500 Best Paper Prize🏆 sponsored independently by Google and Apple
View Accepted Papers
